Dimensions overall score 4.0

• Existing datasets for Binary Function Similarity Detection are limited in scope and fail to reflect real-world diversity.limitation 90%
• EXHIB benchmark comprises five realistic datasets collected from the wild, each highlighting a distinct aspect of the BFSD problem space.method 95%
• Performance degradations of up to 30% occur on firmware and semantic datasets compared to standard settings.result 85%
• Robustness to low- and mid-level binary variations does not generalize to high-level semantic differences.technical 90%
• Current BFSD evaluation practices have a critical blind spot regarding generalization to diverse real-world scenarios.limitation 85%
• Researchers have struggled to compare different BFSD models effectively due to lack of comprehensive universal benchmark.limitation 90%
• EXHIB reveals substantial generalization gaps in current BFSD models.result 85%

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